This invention relates to machine vision, and particularly to machine vision using sub-models.
During PCB assembly, a circuit board is populated with electrically conductive components such as resistors, connectors, and ball grid array devices. The main goal of placing these components is to ensure that they make contact with electrically conductive solder paste that has been dispensed on the PCB, since the components are small and the connections between them are of very fine resolution. The placement of these parts, therefore, must be done with subpixel accuracy.
To accurately place these components, two items of information are needed. The first item is the location of the printed circuit board, and the second item is the location of the device being placed. The location of the printed circuit board is determined using fiducial marks that are machined on the board during the board manufacturing process. These marks must be accurately located to determine the position of the board with respect to the mechanical device placing the components.
Previous methods for locating fiducial marks on PCBs may have several limitations. These methods use correlation-based techniques that are not very robust when exposed to non-linear lighting changes, degraded fiducial marks, or fiducial marks that are smaller or larger than expected.
In one general aspect, the invention is a method for finding a pose of a geometric model of a fiducial mark within an image of a scene containing the fiducial mark. The method includes receiving input from a user including geometric model shape information and geometric model dimensions, selecting a pre-defined model having sub-models by using the model shape information, the pre-defined model being parameterized by the geometric model dimensions; and then using the pre-defined model to find an image of the fiducial mark in the image of the scene.
In a preferred embodiment, the act of selecting a pre-defined model having sub-models includes pre-defining a model such that the sub-models and the relationships among the sub-models are selected by exploiting knowledge of features and properties of the fiducial sought so as to provide more accurate location of the fiducial.
In an alternate preferred embodiment, selecting a pre-defined model having sub-models includes selecting a pre-defined model having sub-models from the group consisting of the pre-defined models shown in FIGS. 2 through 8, inclusive.
In yet another preferred embodiment, the image of the fiducial mark in the image of the scene that was found is measured to provide found fiducial measurements, and the found fiducial measurements are compared with at least one tolerance range.
Thus, the invention provides enhanced ease of use of a sub-model-based search method by requiring only the shape and dimensions of the fiducial sought. An appropriate model and it""s sub-models are automatically provided. The model and it""s sub-models are particularly appropriate to the application when they are based on knowledge of the variability of the fiducial, and other aspect of the behavior of the fiducial throughout a manufacturing process, for example.
The present invention uses the sub-model-based shape finder (also called the Sub-model Search Tool), as described in co-pending U.S. patent application Ser. No. 09/054,968, filed Apr. 3, 1998, entitled xe2x80x9cObject Image Search Using SubModelsxe2x80x9d, herein incorporated by reference, to provide more accurate and robust fiducial mark location than can typically be provided by correlation-based search techniques. Because the method of the invention exploits a robust feature extraction method, such as PatMax or CNLPAS, both sold by Cognex Corporation, it is capable of robustly locating fiducial marks under a wide variety of degraded image conditions. Thus, the present invention can find fiducials in images with non-linear lighting changes, or in images where some fiducials are partially obscured. In addition, a fiducial mark can be located in an image even if the scale of the mark is significantly different from the one being sought. Since the method of the invention uses sub-models to find fiducials, a fiducial can be located with higher accuracy than previous gray-scale correlation techniques, such as normalized correlation search.
In addition to the accuracy and robustness qualities achieved by the use of the sub-model-based shape search technique, the fiducial-finding method of the invention provides a user with the ability to describe fiducial marks not only as a region of an image, but also by its shape and geometric dimensions. The use of sub-models means that the ideal appearance of the fiducial is described and then used as the basis for finding fiducials in subsequent images. If image models are used, the model definition includes any extraneous features that appear in the particular instance of the fiducial mark. Subsequent images of fiducials might include different features produced by changes in lighting or produced by blemishes introduced in fiducial mark etching. These new features can impact the robustness with which the image""s model can be located in subsequent images. By contrast, when a geometric model is used, unimportant and inconsistent features are avoided when describing the fiducial mark. Therefore, these unimportant and inconsistent features do not influence the location of the fiducial in subsequent images.
The use of geometric models by the method of the invention provides certain further benefits and advantages. Using a description of the geometry of a fiducial to be located allows selection and use of the features that are known to be reliably located under different machining conditions. Features of a fiducial that are subject to degradation, or that may be widely varying due to etching conditions, can thereby be ignored. In addition, non-linear changes in the fiducial""s geometry can be described in the fiducial model. In this way, the method of the invention can be used with a robust search technique similar to PatMax, or similar to CNLPAS, both sold by Cognex Corporation, Natick Mass., under conditions where simply locating boundary features would be highly unreliable.
Using geometric models and sub-models also improves the accuracy of the known location of a found fiducial mark. Once a fiducial mark is located in an image, it""s position is used to compute the board location. The position of the fiducial must be determined with respect to a physical frame of reference in order to compute the board location in this way. Since the center of a geometric model can be computed mathematically, its position can be determined more accurately than the position of an image model where the reference point is located manually in an image.